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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-231
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 14 Aug 2018

Research article | 14 Aug 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Stochastic generation of spatially coherent river discharge peaks for large-scale, event-based flood risk assessment

Dirk Diederen1, Ye Liu1, Ben Gouldby1, Ferdinand Diermanse2, and Sergiy Vorogushyn3 Dirk Diederen et al.
  • 1HR Wallingford, Crowmarsh Gifford, UK
  • 2Deltares, Delft, the Netherlands
  • 3GFZ German Research Centre for Geosciences, Potsdam, Germany

Abstract. Flood risk assessments are required for long-term planning, e.g. for investments in infrastructure and other urban capital. Vorogushyn et al. (2018) call for new methods in large-scale Flood Risk Assessment (FRA) to enable the capturing of system interactions and feedbacks. With the increase of computational power, large-scale, continental FRAs have recently become feasible (Ward et al., 2013; Alfieri et al., 2014; Dottori et al., 2016; Vousdoukas, 2016; Winsemius et al., 2016; Paprotny et al., 2017).

Flood events cause large damages worldwide (Desai et al., 2015). Moreover, widespread flooding can potentially cause large damage in a short time window. Therefore, large-scale (e.g. pan-European) events and for instance maximum probable damages are of interest, in particular for the (re)insurance industry, because they want to know the chance of their widespread portfolio of assets getting affected by large-scale events (Jongman et al., 2014). Using a pan-European data set of modelled, gridded river discharge data, we tracked discharge waves in all major European river basins. We synthetically generated a large catalogue of synthetic, pan-European events, consisting of spatially coherent discharge peak sets.

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Floods affect many communities and cause large damage worldwide. Since we choose to live in natural flood plains and are unable to prevent all floods, a system of insurance and re-insurance was set up. For these institutes to not fail, estimates are required of the frequency of large-scale flood events. We explore a new method to obtain a large catalogue of synthetic, spatially-coherent, large-scale river discharge events, using a recent (gridded) European discharge data set.
Floods affect many communities and cause large damage worldwide. Since we choose to live in...
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